adsf

app.py

@@ -266,16 +266,18 @@ def getDates():
 
 def sthlm(streetName, number, sqm, rooms, monthlyFee, monthlyCost, floor, yearBuilt, auto):
     lat, lon = getAddressInfo(streetName, number)
-
+    print('1')
     # If none
     if lat is None or lon is None:
         return '', 'Address not found in the OpenStreetMap dataset (Nominatim), please try another address'
+    print('2')
 
     agency = 'Notar' # Make fun if categorical works
     brf = 'BRF Kartboken 1' # TODO: remove
     dates = getDates()
     input_variables = pd.DataFrame(
             columns=columnHeaders)
+    print('3')
     
     for soldDate in dates.keys():
         # gdp, unemployment, interestRate = getFinancialInfo(soldDate)
@@ -285,9 +287,12 @@ def sthlm(streetName, number, sqm, rooms, monthlyFee, monthlyCost, floor, yearBu
         input_variables = input_variables.append(
             pd.DataFrame(
                 [[streetName,number,sqm,rooms,soldDate,monthlyFee,monthlyCost,floor,yearBuilt,brf,agency,lat,lon]], columns=columnHeaders))
+    print('4')
     
     df = populateApartmentData(input_variables)  
+    print('5')
     df = normalizeData(df)
+    print('6')
     df = xgbFix(df)
 
     pricePred = None
@@ -295,7 +300,9 @@ def sthlm(streetName, number, sqm, rooms, monthlyFee, monthlyCost, floor, yearBu
         # pricePred = autoPred(df)
         '', 'Autogluon is not working right now, please try again later'
     else:
+        print('7')
         pricePred = xgboostPred(df)
+        print('8')
 
     explanations = list(dates.values())
     result = []